Presentation Slides

Presentation Slides

If you re-use any of the follow material, you are agreeing to acknowledge the authors of the presentations. 

Monday, June 22, 2020

Building a Strong Foundation: Defining ML Problems and Preprocessing - David John Gagne - NCAR

Machine Learning Fundamentals - Dorit Hammerling - Colorado School of Mines

Decision Trees and Ensembles - Ryan Lagerquist - University of Oklahoma

Hackathon Intro - David John Gagne - NCAR

Tuesday, June 23, 2020

Convolutional Neural Networks - Karthik Kashinath - Lawrence Berkeley National Laboratory

Recurrent Neural Networks and LSTMs - Chaopeng Shen - Penn State University

Deep Learning Architectures - David Hall - NVIDIA

Wednesday, June 24, 2020

ML in Weather Forecasting Systems - Sue Ellen Haupt - NCAR

ML for Segmentation of Atmospheric Phenomena - Jebb Stewart - NOAA ESRL

ML Emulators in Land Surface Models - Katie Dagon - NCAR

Thursday, June 25, 2020

Peering Inside the Black Box of Machine Learning for Earth Science - Part 1 - Amy McGovern - University of Oklahoma

Peering Inside the Black Box of Machine Learning for Earth Science - Part 2 - Imme Ebert-Uphoff - Colorado State University/CIRA

ML Parameterization - Mike Pritchard - UC Irvine

Friday, June 26, 2020

Generative Models - Mustafa Mustafa - Lawrence Berkeley National Laboratory

Physics-Guided ML - Pierre Gentine - Columbia University

Deep Unsupervised Learning for Climate Applications - Claire Monteleoni - University of Colorado Boulder